Multipronged quantitative proteomics reveals serum proteome alterations in breast cancer intrinsic subtypes

Realm of proteomics in breast cancer management and drug repurposing to alleviate intricacies of treatment

Breast cancer, a multi-networking heterogeneous disease, has emerged as a serious impediment to progress in clinical oncology. Although technological advancements and emerging cancer research studies have mitigated breast cancer lethality, a precision cancer-oriented solution has not been achieved. Thus, this review will persuade the acquiescence of proteomics-based diagnostic and therapeutic options in breast cancer management. Recently, the evidence of breast cancer health surveillance through imaging proteomics, single-cell proteomics, interactomics, and post-translational modification (PTM) tracking, to construct proteome maps and proteotyping for stage-specific and sample-specific cancer subtyping have outperformed conventional ways of dealing with breast cancer by increasing diagnostic efficiency, prognostic value, and predictive response. Additionally, the paradigm shift in applied proteomics for designing a chemotherapy regimen to identify novel drug targets with minor adverse effects has been elaborated. Finally, the potential of proteomics in alleviating the occurrence of chemoresistance and enhancing reprofiled drugs' effectiveness to combat therapeutic obstacles has been discussed. Owing to the enormous potential of proteomics techniques, the clinical recognition of proteomics in breast cancer management can be achievable and therapeutic intricacies can be surmountable.

Study on the Relationship Between Differentially Expressed Proteins in Breast Cancer and Lymph Node Metastasis

INTRODUCTION

Lymph node metastasis is a cause of poor prognosis in breast cancer. Mass spectrometry-based proteomics aims to map the protein landscapes of biological samples and profile tumors more comprehensively. Here, proteomics was employed to identify differentially expressed proteins (DEPs) that were associated with lymph node metastasis.

METHODS

Tandem mass tag (TMT) quantitative proteomic approaches were applied for extensive profiling of conditioned medium of MDA-MB-231 and MCF7 cell lines and serums of patients who did or did not have lymph node metastasis, and DEPs were analyzed by bioinformatics. Furthermore, potential secreted or membrane proteins MUC5AC, ITGB4, CTGF, EphA2, S100A4, PRDX2, and PRDX6 were selected for verification in 114 tissue microarray samples of breast cancer using the immunohistochemical method. The relevant data was analyzed and processed by independent sample t test, chi-square test, or Fisher's exact test using SPSS 22.0 software.

RESULTS

In the conditioned medium of MDA-MB-231 cell lines, 154 proteins were upregulated, while 136 were downregulated compared to those of MCF7. In the serum of patients with breast cancer and lymph node metastasis, 17 proteins were upregulated, and 5 proteins were downregulated compared to those without lymph node metastasis. Furthermore, according to tissue verification, CTGF, EphA2, S100A4, and PRDX2 were associated with breast cancer lymph node metastasis.

CONCLUSION

Our study provides a new perspective for the understanding of the role of DEPs (especially CTGF, EphA2, S100A4, and PRDX2) in the development and metastasis of breast cancer. They could become potential diagnostic and prognostic biomarkers and therapeutic targets.

Clinical application of serum-based proteomics technology in human tumor research

The rapid development of proteomics technology in the past decades has led to further human understanding of tumor research, and in some ways, the technology plays a very important supporting role in the early detection of tumors. Human serum has been shown to contain a variety of proteins closely related to life activities, and the dynamic change in proteins can often reflect the physiological and pathological conditions of the body. Serum has the advantage of easy extraction, so the application of proteomics technology in serum has become a hot spot and frontier area for the study of malignant tumors. However, there are still many difficulties in the standardized use of proteomic technologies, which inevitably limit the clinical application of proteomic technologies due to the heterogeneity of human proteins leading to incomplete whole proteome populations, in addition to most serum protein markers being now not highly specific in aiding the early detection of tumors. Nevertheless, further development of proteomics technologies will greatly increase our understanding of tumor biology and help discover more new tumor biomarkers with specificity that will enable medical technology.

Targeted proteomics using parallel reaction monitoring confirms salivary proteins indicative of metastatic triple-negative breast cancer

Triple-negative breast cancer (TNBC) is the most aggressive subtype due to the absence of hormonal receptors. Our study aimed to identify and determine the effectiveness of salivary proteins as candidate markers for metastatic TNBC subtype using parallel reaction monitoring mass spectrometry (PRM-MS). Three salivary proteins (lipocalin-1, SMR3B, and plastin-2) that showed significant differential expression in label-free quantitation (LFQ) between TNBC (N = 6) and health subjects (HS; N = 6) were selected for further validation. The developed PRM assay was used to quantify peptides GLST and NNLE (lipocalin-1), VYAL and MINL (Plastin-2) and GPYP, and IPPP (SMR3B) on a different cohort of TNBC patients (N = 20) and HS (N = 20) for evaluating their discriminating performances. Quantitative validation using PRM correlated well with the LFQ results, and 5 peptides from three proteins showed a similar up-or down-regulation. Subsequently, these proteins were validated by Western blot analysis. Compared to one protein's performance as an individual marker, the five-signature panel with salivary GLST, VYAL, MINL, GPYP, and IPPP achieved better performance in differentiating aggressive TNBC and HS with sensitivity (80%) and specificity (95%). Targeted proteomic analysis of the prioritized proteins highlights a peptide-based signature in saliva as the potential predictor to distinguish between TNBC and HS. SIGNIFICANCE OF THE STUDY: This study was designed to identify and quantify potential markers in saliva from the triple-negative breast cancer (TNBC) patients using parallel reaction monitoring assay. Three salivary proteins, Lipocalin-1 (LCN-1), Submaxillary androgen-regulated protein 3B (SMR3B), and Plastin-2 (LCP-1) selected in the discovery-phase were further quantified by targeted proteomics and Western blots. The salivary proteins successfully differentiated TNBC patients from healthy subjects with a sensitivity (80%) and specificity (95%).

Circulating proteins reveal prior use of menopausal hormonal therapy and increased risk of breast cancer

Accessible risk predictors are crucial for improving the early detection and prognosis of breast cancer. Blood samples are widely available and contain proteins that provide important information about human health and disease, however, little is still known about the contribution of circulating proteins to breast cancer risk prediction. We profiled EDTA plasma samples collected before diagnosis from the Swedish KARMA breast cancer cohort to evaluate circulating proteins as molecular predictors. A data-driven analysis strategy was applied to the molecular phenotypes built on 700 circulating proteins to identify and annotate clusters of women. The unsupervised analysis of 183 future breast cancer cases and 366 age-matched controls revealed five stable clusters with distinct proteomic plasma profiles. Among these women, those in the most stable cluster (N = 19; mean Jaccard index: 0.70 ± 0.29) were significantly more likely to have used menopausal hormonal therapy (MHT), get a breast cancer diagnosis, and were older compared to the remaining clusters. The circulating proteins associated with this cluster (FDR < 0.001) represented physiological processes related to cell junctions (F11R, CLDN15, ITGAL), DNA repair (RBBP8), cell replication (TJP3), and included proteins found in female reproductive tissue (PTCH1, ZP4). Using a data-driven approach on plasma proteomics data revealed the potential long-lasting molecular effects of menopausal hormonal therapy (MHT) on the circulating proteome, even after women had ended their treatment. This provides valuable insights concerning proteomics efforts to identify molecular markers for breast cancer risk prediction.

High-throughput proteomics of breast cancer interstitial fluid: identification of tumor subtype-specific serologically relevant biomarkers

Despite significant advancements in breast cancer (BC) research, clinicians lack robust serological protein markers for accurate diagnostics and tumor stratification. Tumor interstitial fluid (TIF) accumulates aberrantly externalized proteins within the local tumor space, which can potentially gain access to the circulatory system. As such, TIF may represent a valuable starting point for identifying relevant tumor-specific serological biomarkers. The aim of the study was to perform comprehensive proteomic profiling of TIF to identify proteins associated with BC tumor status and subtype. A liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis of 35 TIFs of three main subtypes: luminal (19), Her2 (4), and triple-negative (TNBC) (12) resulted in the identification of > 8800 proteins. Unsupervised hierarchical clustering segregated the TIF proteome into two major clusters, luminal and TNBC/Her2 subgroups. High-grade tumors enriched with tumor infiltrating lymphocytes (TILs) were also stratified from low-grade tumors. A consensus analysis approach, including differential abundance analysis, selection operator regression, and random forest returned a minimal set of 24 proteins associated with BC subtypes, receptor status, and TIL scoring. Among them, a panel of 10 proteins, AGR3, BCAM, CELSR1, MIEN1, NAT1, PIP4K2B, SEC23B, THTPA, TMEM51, and ULBP2, was found to stratify the tumor subtype-specific TIFs. In particular, upregulation of BCAM and CELSR1 differentiates luminal subtypes, while upregulation of MIEN1 differentiates Her2 subtypes. Immunohistochemistry analysis showed a direct correlation between protein abundance in TIFs and intratumor expression levels for all 10 proteins. Sensitivity and specificity were estimated for this protein panel by using an independent, comprehensive breast tumor proteome dataset. The results of this analysis strongly support our data, with eight of the proteins potentially representing biomarkers for stratification of BC subtypes. Five of the most representative proteomics databases currently available were also used to estimate the potential for these selected proteins to serve as putative serological markers.

Protein Corona Gold Nanoparticles Fingerprinting Reveals a Profile of Blood Coagulation Proteins in the Serum of HER2-Overexpressing Breast Cancer Patients

Breast cancer (BC) is a molecularly heterogeneous disease that encompasses five major molecular subtypes (luminal A (LA), luminal B HER2 negative (LB-), luminal B HER2 positive (LB+), HER2 positive (HER2+) and triple negative breast cancer (TNBC)). BC treatment mainly depends on the identification of the specific subtype. Despite the correct identification, therapies could fail in some patients. Thus, further insights into the genetic and molecular status of the different BC subtypes could be very useful to improve the response of BC patients to the range of available therapies. In this way, we used gold nanoparticles (AuNPs, 12.96 ± 0.72 nm) as a scavenging tool in combination with Sequential Window Acquisition of All Theoretical Mass Spectra (SWATH-MS) to quantitatively analyze the serum proteome alterations in the different breast cancer intrinsic subtypes. The differentially regulated proteins specific of each subtype were further analyzed with the bioinformatic tools STRING and PANTHER to identify the major molecular function, biological processes, cellular origin, protein class and biological pathways altered due to the heterogeneity in proteome of the different BC subtypes. Importantly, a profile of blood coagulation proteins was identified in the serum of HER2-overexpressing BC patients.

iTRAQ-based quantitative proteomic analysis of peripheral blood serum in piglets infected with Actinobacillus pleuropneumoniae

Porcine pleuropneumonia caused by Actinobacillus pleuropneumoniae (APP) is a swine respiratory disease with an important impact around the world either as a single infection or part of the porcine respiratory disease complex. The data of interaction between hosts and pathogens has becoming more crucial for exploration of the mechanism. However, up to now, comparatively little information is available on the systemic and dynamic changes that occur in pig serum in response to APP infection. This study used iTRAQ to identify differentially expressed proteins (DEPs) in pig serum in response to APP infection. Compared with the APP un-infected group (S0),there were 137 up-regulated and 68 down-regulated proteins at 24 h (S24), and 81 up-regulated and 107 down-regulated proteins at 120 h (S120). At 24 h, the immune response was not significantly enriched, but cell adhesion, cytosol, Golgi apparatus, GTP and ATP binding and regulation of cell cycle were extremely active, implying host preparation of immune response starting. Subsequently, innate immune response, negative regulation of apoptotic process, immunological synapse, adaptive immune response, the regulation of inflammatory response, positive regulation of T cell proliferation were more enhanced at 120 h then that of 24 h, representing innate immunity transferring to the adaptive, while endocytosis, cell adhesion and platelet aggregation showed obvious decline. The pathways of T cell receptor signaling pathway, cytokine–cytokine receptor interaction, complement and coagulation cascades, leukocyte transendothelial migration were active remarkably during all infection period, and more pathways could connect to form innate immune defense networks. Surprisingly, the pathways like amoebiasis, rheumatoid arthritis and malaria had been found up-regulated. As a conclusion, APP could delay host inflammatory response to the infection at early stage, and induced innate immunity to convert from adhesion, interaction into complement activation, proteasome digestion, bacterial invasion at later stage. This would increase our understanding of the porcine distinct response to APP infection.

The development and clinical applications of proteomics: an Indian perspective

INTRODUCTION

Proteomic research has been extensively used to identify potential biomarkers or targets for various diseases. Advances in mass spectrometry along with data analytics have led proteomics to become a powerful tool for exploring the critical molecular players associated with diseases, thereby, playing a significant role in the development of proteomic applications for the clinic.

AREAS COVERED

This review presents recent advances in the development and clinical applications of proteomics in India toward understanding various diseases including cancer, metabolic diseases, and reproductive diseases. Keywords combined with 'clinical proteomics in India' 'proteomic research in India' and 'mass spectrometry' were used to search PubMed.

EXPERT OPINION

The past decade has seen a significant increase in research in clinical proteomics in India. This approach has resulted in the development of proteomics-based marker technologies for disease management in the country. The majority of these investigations are still in the discovery phase and efforts have to be made to address the intended clinical use so that the identified potential biomarkers reach the clinic. To move toward this necessity, there is a pressing need to establish some key infrastructure requirements and meaningful collaborations between the clinicians and scientists which will enable more effective solutions to address health issues specific to India.

Identification of a Profile of Neutrophil-Derived Granule Proteins in the Surface of Gold Nanoparticles after Their Interaction with Human Breast Cancer Sera

It is well known that the interaction of a nanomaterial with a biological fluid leads to the formation of a protein corona (PC) surrounding the nanomaterial. Using standard blood analyses, alterations in protein patterns are difficult to detect. PC acts as a “nano-concentrator” of serum proteins with affinity for nanoparticles’ surface. Consequently, characterization of PC could allow detection of otherwise undetectable changes in protein concentration at an early stage of a disease, such as breast cancer (BC). Here, we employed gold nanoparticles (AuNPs_diameter: 10.02 ± 0.91 nm) as an enrichment platform to analyze the human serum proteome of BC patients (n = 42) and healthy controls (n = 42). Importantly, the analysis of the PC formed around AuNPs after their interaction with serum samples of BC patients showed a profile of proteins that could differentiate breast cancer patients from healthy controls. These proteins developed a significant role in the immune and/or innate immune system, some of them being neutrophil-derived granule proteins. The analysis of the PC also revealed serum proteome alterations at the subtype level.

Proteomics and functional study reveal marginal zone B and B1 cell specific protein as a candidate marker of multiple myeloma

Multiple myeloma (MM) is a plasma cell‑associated cancer and accounts for 13% of all hematological malignancies, worldwide. MM still remains an incurable plasma cell malignancy with a poor prognosis due to a lack of suitable markers. Therefore, discovering novel markers and targets for diagnosis and therapeutics of MM is essential. The present study aims to identify markers associated with MM malignancy using patient‑derived MM mononuclear cells (MNCs). Label‑free quantitative proteomics analysis revealed a total of 192 differentially regulated proteins, in which 79 proteins were upregulated and 113 proteins were found to be downregulated in MM MNCs as compared to non‑hematological malignant samples. The identified differentially expressed candidate proteins were analyzed using various bioinformatics tools, including Ingenuity Pathway Analysis (IPA), Protein Analysis THrough Evolutionary Relationships (PANTHER), Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and Database for Annotation, Visualization and Integrated Discovery (DAVID) to determine their biological context. Among the 192 candidate proteins, marginal zone B and B1 cell specific protein (MZB1) was investigated in detail using the RPMI-8226 cell line model of MM. The functional studies revealed that higher expression of MZB1 is associated with promoting the progression of MM pathogenesis and could be established as a potential target for MM in the future.

Quantitative Comparative Proteomics Reveal Biomarkers for Dengue Disease Severity

Dengue fever (DF) could develop into dengue haemorrhagic fever (DHF) with increased mortality rate. Since the clinical characteristics and pathogen are same in DF and DHF. It's important to identify different molecular biomarkers to predict DHF patients from DF. We conducted a clinical plasma proteomics study using quantification (TMT)-based quantitative proteomics methodology to found the differential expressed protein in DF patients before they developed into DHF. In total 441 proteins were identified up or down regulated. There proteins are enriched in diverse biological processes such as proteasome pathway, Alanine, aspartate, and glutamate metabolism and arginine biosynthesis. Several proteins such as PLAT, LAMB2, and F9 were upregulated in only DF patients which developed into DHF cases, not in DF, compared with healthy-control. In another way, FGL1, MFAP4, GLUL, and VCAM1 were upregulated in both DHF and DF cases compare with healthy-control. RT-PCR and ELISA were used to validate these upregulated gene expression and protein level in 54 individuals. Results displayed the same pattern as proteomics analysis. All including PLAT, LAMB2, F9, VCAM1, FGL1, MFAP4, and GLUL could be considered as potential markers of predicting DHF since the levels of these proteins vary between DF and DHF. These new founding identified potential molecular biomarkers for future development in precision prediction of DHF in DF patients.

Mining cancer biology through bioinformatic analysis of proteomic data

Introduction: Discovery proteomics for cancer research generates complex datasets of diagnostic, prognostic, and therapeutic significance in human cancer. With the advent of high-resolution mass spectrometers, able to identify thousands of proteins in complex biological samples, only the application of bioinformatics can lead to the interpretation of data which can be relevant for cancer research. Areas covered: Here, we give an overview of the current bioinformatic tools used in cancer proteomics. Moreover, we describe their applications in cancer proteomics studies of cell lines, serum, and tissues, highlighting recent results and critically evaluating their outcomes. Expert opinion: The use of bioinformatic tools is a fundamental step in order to manage the large amount of proteins (from hundreds to thousands) that can be identified and quantified in a cancer biological samples by proteomics. To handle this challenge and obtain useful data for translational medicine, it is important the combined use of different bioinformatic tools. Moreover, a particular attention to the global experimental design, and the integration of multidisciplinary skills are essential for best setting of tool parameters and best interpretation of bioinformatics output.

Blood-based protein biomarkers in breast cancer

Breast cancer (BCa) is a significant healthcare problem on women worldwide. Thus, early detection is very important to reduce mortality. Furthermore, better BCa prognosis could improve selection of patients eligible for adjuvant therapy. New markers for early diagnosis, accurate prognosis and prediction of response to treatment are necessary to improve BCa care. The present review summarizes important aspects of the potential usefulness of modern technologies, strategies, and scientific findings in proteomic research for discovery of breast cancer-associated blood-based protein biomarkers in the clinic.

Exploring the Potential of Data-Independent Acquisition Proteomics Using Untargeted All-Ion Quantitation: Application to Tumor Subtype Diagnosis

Maximizing the recovery of meaningful biological information can facilitate proteomics-guided early detection and precise treatment of diseases. However, the conventional protein and peptide level targeted quantification of untargeted data independent acquisition (DIA) such as sequential window acquisition of all theoretical spectra (SWATH) is not necessarily descriptive of all information. Untargeted all-ion quantification theoretically could retrieve more features in SWATH digital maps by circumventing the initial identification process but is intrinsically susceptible to errors because of the extreme complexity of proteome samples and the poor selectivity of a single ion. In this study, we optimized and applied the untargeted all-ion quantification of SWATH data to differentiate tumor subtypes. Large peptides and low abundant peptides benefited more from untargeted all-ion quantification. Top-ranked significant ions were linked to their corresponding ion envelops, where multiple correlated ions were used for measurement and only ion envelopes containing at least three ions with consistent intensity ratio were kept as refined differentiating features. Multivariate statistical analysis revealed that for the tested data set, the refined markers discovered by untargeted SWATH analysis showed comparable diagnostic power to protein and peptide markers. Limitations and benefits of the approach are further discussed.